Interacting with flying objects has fueled people’s imagination throughout history. Over the past decade, the Human-Drone Interaction (HDI) community has been working towards making this dream a reality. Despite notable findings, we lack a high-level perspective on the current and future use cases for interacting with drones. We present a holistic view of domains and applications of use that are described, studied, and envisioned in the HDI body of work. To map the extent and nature of the prior research, we performed a scoping review (N=217). We identified 16 domains and over 100 applications where drones and people interact together. We then describe in depth the main domains and applications reported in the literature and further present under-explored use cases with great potential. We conclude with fundamental challenges and opportunities for future research in the field. This work contributes a systematic step towards increased replicability and generalizability of HDI research.

/pdf/above-and-beyond-a-scoping-review-of-domains-and-2qe0hvkx.pdf

Above and Beyond: A Scoping Review of Domains and Applications for Human-Drone Interaction

Reinforcement learning (RL) methods have been actively applied in the field of robotics, allowing the system itself to find a solution for a task otherwise requiring a complex decision-making algorithm. In this paper, we present a novel RL-based Tic-tac-toe scenario, i.e. SwarmPlay, where each playing component is presented by an individual drone that has its own mobility and swarm intelligence to win against a human player. Thus, the combination of challenging swarm strategy and human-drone collaboration aims to make the games with machines tangible and interactive. Although some research on AI for board games already exists, e.g., chess, the SwarmPlay technology has the potential to offer much more engagement and interaction with the user as it proposes a multi-agent swarm instead of a single interactive robot. We explore user’s evaluation of RL-based swarm behavior in comparison with the game theory-based behavior. The preliminary user study revealed that participants were highly engaged in the game with drones (70% put a maximum score on the Likert scale) and found it less artificial compared to the regular computer-based systems (80%). The affection of the user’s game perception from its outcome was analyzed and put under discussion. User study revealed that SwarmPlay has the potential to be implemented in a wider range of games, significantly improving human-drone interactivity.

SwarmPlay: Interactive Tic-tac-toe Board Game with Swarm of Nano-UAVs driven by Reinforcement Learning

Design of a class of generalized parallel mechanisms for adaptive landing and aerial manipulation

Light painting photos are created by moving light sources in mid-air while taking a long exposure photo. However, it is challenging for novice users to leave accurate light traces without any spatial guidance. Therefore, we present LightPaintAR, a novel interface that leverages augmented reality (AR) traces as a spatial reference to enable precise movement of the light sources. LightPaintAR allows users to draft, edit, and adjust virtual light traces in AR, and move light sources along the AR traces to generate accurate light traces on photos. With LightPaintAR, users can light paint complex patterns with multiple strokes and colors. We evaluate the effectiveness and the usability of our system with a user study and showcase multiple light paintings created by the users. Further, we discuss future improvements of LightPaintAR.

LightPaintAR: Assist Light Painting Photography with Augmented Reality

Robots able to run, fly, and grasp have a high potential to solve a wide scope of tasks and navigate in complex environments. Several mechatronic designs of such robots with adaptive morphologies are emerging. However, the task of landing on an uneven surface, traversing rough terrain, and manipulating objects still presents high challenges.This paper introduces the design of a novel rotor UAV MorphoGear with morphogenetic gear and includes a description of the robot’s mechanics, electronics, and control architecture, as well as walking behavior and an analysis of experimental results. MorphoGear is able to fly, walk on surfaces with several gaits, and grasp objects with four compatible robotic limbs. Robotic limbs with three degrees of freedom (DoFs) are used by this UAV as pedipulators when walking or flying and as manipulators when performing actions in the environment. We performed a locomotion analysis of the landing gear of the robot. Three types of robot gaits have been developed.The experimental results revealed low crosstrack error of the most accurate gait (mean of 1.9 cm and max of 5.5 cm) and the ability of the drone to move with a 210 mm step length. Another type of robot gait also showed low crosstrack error (mean of 2.3 cm and max of 6.9 cm). The proposed MorphoGear system can potentially achieve a high scope of tasks in environmental surveying, delivery, and high-altitude operations.

MorphoGear: An UAV with Multi-Limb Morphogenetic Gear for Rough-Terrain Locomotion

Nowadays, there are few unmanned aerial vehicles (UAVs) that are capable of landing on uneven surfaces or moving on the complex ground. A drone having both of these functionalities can significantly improve its performance in accomplishing difficult tasks, such as monitoring and exploring various types of terrain, searching for survivors, and delivering medical aid or repair kits in an unstructured dynamic environment, e.g., rescue operation following an earthquake. This article presents a motion analysis of the gait of an adaptive landing platform for multicopters. This landing gear has four robotic legs facilitated with torque sensors in the knee joints. Though it had been developed to provide adaptive landing on uneven surfaces, we decided to exploit the system for terrain locomotion purposes. For this purpose, we have analyzed the center of mass trajectory to evaluate the possible trajectory of the robot. Based on the result of this experimental analysis, we propose a LocoGear, a novel algorithm for locomotion of UAV equipped with the robotic landing gear. The servomotor torques were estimated using Lagrangian dynamic formulation and kinetostatic methods. We conducted experiments to verify the LocoGear approach based on feedforward control that proves the capability of landing gear to move along the desired trajectory. We achieved the robot motion along the straight line with the standard deviation of length in each step of 9.8 mm and standard deviation in yaw of 9°.

LocoGear: Locomotion Analysis of Robotic Landing Gear for Multicopters

We propose a novel human-drone interaction paradigm where a user directly interacts with a drone to light-paint predefined patterns or letters through hand gestures. The user wears a glove which is equipped with an IMU sensor to draw letters or patterns in the midair. The developed ML algorithm detects the drawn pattern and the drone light-paints each pattern in midair in the real time. The proposed classification model correctly predicts all of the input gestures. The DroneLight system can be applied in drone shows, advertisements, distant communication through text or pattern, rescue, and etc. To our knowledge, it would be the world's first human-centric robotic system that people can use to send messages based on light-painting over distant locations (drone-based instant messaging). Another unique application of the system would be the development of vision-driven rescue system that reads light-painting by person who is in distress and triggers rescue alarm.

DroneLight: Drone Draws in the Air using Long Exposure Light Painting and ML

In this paper, we propose a novel approach to wheeled robot navigation through an environment with movable obstacles. A robot exploits knowledge about different obstacle classes and selects the minimally invasive action to perform to clear the path. We trained a convolutional neural network (CNN), so the robot can classify an RGB-D image and decide whether to push a blocking object and which force to apply. After known objects are segmented, they are being projected to a cost-map, and a robot calculates an optimal path to the goal. If the blocking objects are allowed to be moved, a robot drives through them while pushing them away. We implemented our algorithm in ROS, and an extensive set of simulations showed that the robot successfully overcomes the blocked regions. Our approach allows a robot to successfully build a path through regions, where it would have stuck with traditional path-planning techniques.

SwipeBot: DNN-based Autonomous Robot Navigation among Movable Obstacles in Cluttered Environments

The festivalization of the creative city: A study of two creative quarters in Barcelona and Berlin

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Nikolay Zherdev

Author Tools

Chat about Author

Papers

LocoGear: Locomotion Analysis of Robotic Landing Gear for Multicopters

DroneLight: Drone Draws in the Air using Long Exposure Light Painting and ML

DroneLight: Drone Draws in the Air using Long Exposure Light Painting and ML

SwipeBot: DNN-based Autonomous Robot Navigation among Movable Obstacles in Cluttered Environments

The festivalization of the creative city: A study of two creative quarters in Barcelona and Berlin